Instructions to use Kibalama/tinyLLms-fine-tuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kibalama/tinyLLms-fine-tuned with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Kibalama/tinyLLms-fine-tuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Kibalama/tinyLLms-fine-tuned: direct link, hf CLI and curl.
- Browser
- Download file 5.62 kB
-
https://huggingface.co/Kibalama/tinyLLms-fine-tuned/resolve/main/training_args.bin
- Command line
-
hf download hf://Kibalama/tinyLLms-fine-tuned/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Kibalama/tinyLLms-fine-tuned/resolve/main/training_args.bin
5.62 kB
- Xet hash:
- 9c195303a35e24f09817cb3e49198ce92707487d560a44e152792f14f8726b69
- Size of remote file:
- 5.62 kB
- SHA256:
- ee43c0d8bb3672a7b5e036f544518421dafea5cf8f8facee7e3023d962960aad
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